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We analysed the full text of all journal articles returned to the education subpanel of the 2021 Research Excellence Framework (REF2021). Using a latent Dirichlet allocation topic model, we identified 35 topics that collectively summarise the journal articles that research units, typically schools of education, selected for submission. We found that the topics which units wrote about in their submitted articles collectively explained a large proportion (84.1%) of the variance in the quality assessments they received from the REF's expert peer review process. Further, with the important caveat that we cannot attribute causality, we found that there were strong associations between what the subpanel perceived to be excellent research and the adoption of particular methods or approaches. Most notably, units that returned more interview-based work typically received lower scores, and those which returned more analyses of large-scale data and meta-analyses typically received higher scores. Finally, we applied our 2021 model to articles submitted to the previous exercise, REF2014. We found that education research seems to have become less qualitative and more quantitative over time, and that our 2021 model could successfully predict the scores assigned by the REF2014 subpanel, suggesting a reasonable degree of between-exercise consistency.

Abstract Hepatocellular carcinoma (HCC) is a molecularly heterogeneous solid malignancy, and its fitness may be shaped by how its tumor cells evolve. However, ability to monitor tumor cell evolution is hampered by the presence of numerous passenger mutations that do not provide any biological consequences. Here we develop a strategy to determine the tumor clonality of three independent HCC cohorts of 524 patients with diverse etiologies and race/ethnicity by utilizing somatic mutations in cancer driver genes. We identify two main types of tumor evolution, i.e., linear, and non-linear models where non-linear type could be further divided into classes, which we call shallow branching and deep branching. We find that linear evolving HCC is less aggressive than other types. GTF2IRD2B mutations are enriched in HCC with linear evolution, while TP53 mutations are the most frequent genetic alterations in HCC with non-linear models. Furthermore, we observe significant B cell enrichment in linear trees compared to non-linear trees suggesting the need for further research to uncover potential variations in immune cell types within genomically determined phylogeny types. These results hint at the possibility that tumor cells and their microenvironment may collectively influence the tumor evolution process.

There is a norm in psychology to use causally ambiguous statistical language, rather than straightforward causal language, when describing methods and results of nonexperimental studies. However, causally ambiguous language may inhibit a critical examination of the studys causal assumptions and lead to a greater acceptance of policy recommendations that rely on causal interpretations of nonexperimental findings. In a preregistered experiment, 142 psychology faculty, postdocs, and doctoral students (54% female), ages 22-67 (M = 33.20, SD = 8.96), rated the design and analysis from hypothetical studies with causally ambiguous statistical language as of higher quality (by .34-.80 SD) and as similarly or more supportive (by .16-.27 SD) of policy recommendations than studies described in straightforward causal language. Thus, using statistical rather than causal language to describe nonexperimental findings did not decrease, and may have increased, perceived support for implicitly causal conclusions.

Abstract Indigenous People and Local Communities (IPLC) can play an important role in reforestation for climate change mitigation while providing environmental and livelihood benefits. However, there is a lack of direct comparison between different reforestation design's carbon uptake potential and their relevance to community reforestation. We evaluate the carbon capture and survival of the four most common reforestation designs in a 14‐year‐long project in an Emberá community in eastern Panama. We look at native timber mixtures and monocultures, agroforestry, and natural regrowth with enrichment planting. To explain the differences between plots, we compare design, management and environmental characteristics using redundancy analyses (RDA). We then contextualize our results with the project leader's perspectives of success using interviews and workshops. In the first decade, mixtures and monocultures of timber stored on average roughly 3× more carbon than agroforestry and enrichment planting (140 tCO2/ha compared to 40 tCO2/ha and 53 tCO2/ha). The project design had the largest influence on carbon storage and survival with an explanatory power of 31% followed by management and environmental characteristics (14% and 2% respectively). The largest threat to the survival and growth was the risk of fire which caused mortality in more than 2/3 of the plots. Some damage was offset by natural regrowth which accounted for 34% of the total carbon, but the participants generally perceived natural regrowth as being “dirty.” They had a strong preference for agroforestry, particularly coffee (Coffea spp.), a crop with negligible carbon value, but high economic value. ‘Practical implication’: The findings underscore the need to balance carbon sequestration with local economic preferences, integrate community input, mitigate environmental risks and adopt long‐term, holistic approaches for effective reforestation projects.

The flipped classroom (FC) is becoming an increasingly popular teaching method in mathematics education. However, few studies have rigorously evaluated its effectiveness, and less so in countries where students' level of mathematics achievement is low. In this study, we evaluated the impact of an FC intervention in Saudi Arabia, the country with the lowest level of maths achievement in the last iteration of the Trends International Mathematics and Science Study TIMSS . A total of 281 secondary school students received eight weeks of algebra training using either FC or traditional instruction, and were tested on algebra problems taken from past national standardised tests, as well as on a measure of self-efficacy. Students who received the intervention showed higher self-efficacy but no significant difference in maths achievement was observed. Students' and teachers' perceptions of the intervention were positive.

Randomized controlled trials have proliferated in education, in part because they provide an unbiased estimator for the causal impact of interventions. It is increasingly recognized that many such trials in education have low power to detect an effect if indeed there is one. However, it is less well known that low powered trials tend to systematically exaggerate effect sizes among the subset of interventions that show promising results (p < [alpha]) We conduct a retrospective design analysis to quantify this bias across 22 such promising trials, finding that the estimated effect sizes are exaggerated by an average of 52% or more. Promising trial bias can be reduced ex-ante by increasing the power of the trials that are commissioned and guarded against ex-post by including estimates of the exaggeration ratio when reporting trial findings. Our results also suggest that challenges around implementation fidelity are not the only reason that apparently successful interventions often fail to subsequently scale up. Instead, the effect from the initial promising trial may simply be exaggerated.

Many assessment models (AMs) supporting the evaluation of Building Information Modeling (BIM) deployment within an organization or a project have recently been developed. However, it has become challenging to choose which AM is best suited to meet a user's needs in a specific context. These AMs use different criteria and apply different theoretical bases. Moreover, many have been developed with little industry involvement, feedback being given through surveys and focus groups. Lastly, they generally do not consider the context in which the assessment takes place. This paper presents a framework for a type 3 meta-evaluation assessing BIM-AMs concerning their effectiveness, relevance, and usefulness in the context in which they will be implemented. As a contribution to theory, it incorporates the criteria for BIM evaluation developed by Succar et al. (2012) and psychometric validities to evaluate theoretically different models and to incorporate industry input. As a contribution to practice, the framework was used to evaluate two BIM-AMs and provide suggestions for their improvement. Key words: BIM assessment models, BIM maturity, BIM competency, meta-evaluation framework, evaluation, 1. Introduction The construction industry is undergoing a transformation driven through the introduction of digital tools and technologies, namely by implementing new approaches such as Building Information Modeling (BIM). BIM [...]

Summary: Primary liver cancer (PLC) consists of two main histological subtypes; hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). The role of transcription factors (TFs) in malignant hepatobiliary lineage commitment between HCC and iCCA remains underexplored. Here, we present genome-wide profiling of transcription regulatory elements of 16 PLC patients using single-cell assay for transposase accessible chromatin sequencing. Single-cell open chromatin profiles reflect the compositional diversity of liver cancer, identifying both malignant and microenvironment component cells. TF motif enrichment levels of 31 TFs strongly discriminate HCC from iCCA tumors. These TFs are members of the nuclear/retinoid receptor, POU, or ETS motif families. POU factors are associated with prognostic features in iCCA. Overall, nuclear receptors, ETS and POU TF motif families delineate transcription regulation between HCC and iCCA tumors, which may be relevant to development and selection of PLC subtype-specific therapeutics.

Multiregion sequencing is needed to better capture the heterogeneity of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Here, the authors analyse HCC and iCCA tumours with multiregion single-cell RNA-seq, revealing cellular dynamics and communication networks with immune cells.

During pandemics, in which harm is universal, states find themselves under an obligation to cooperate within a global solidarity framework. However, because they do not have the same set of capabilities, their obligations should be differentiated and based on equity and distributive justice. As an effective tool of States' foreign policy, health diplomacy is being used by developing countries according to different priorities and interests. After a few months of relative calm, COVID-19 still poses a major challenge for African and Middle Eastern economies and societies where the vaccination rates are low across the board with healthcare systems in poor shape. If some Gulf countries can be considered exceptions due to active lockdowns, mobility restrictions, and considerable testing, their engagement abroad to help contain the pandemic, especially in North Africa, shows that, if the spirit of cooperation and justice is well taken care of at the regional level, this is not the case at the international level, where global health cooperation would clearly benefit from the application of a type of differentiated treatment such as the one provided by the Common but Differentiated Responsibilities (CBDR) principle. Keywords: Health diplomacy, Vaccines, CBDR, Principle, Cooperation, Introduction Contrary to a global public good (2), a so-called 'global public harm (3)' is linked to a damage and not to the consumption of a good. To constitute a [...]

Research findings regarding the effects of educational interventions--typically reported in units of standard deviations (e.g., Cohen's d)--are often translated into more intuitive metrics before being communicated to teachers. However, there is no consensus about the most suitable metric, and no study has systematically examined how teachers respond to the different options. We conducted two preregistered studies addressing this issue. We found that teachers have strong preferences concerning effect size metrics in terms of informativeness, understandability, and helpfulness. These preferences challenge current research reporting recommendations. Most importantly, we found that different metrics induce different perceptions of an intervention's effectiveness--a situation that could cause teachers to have unrealistic expectations about what a given intervention may achieve. Implications for how educational effects should be communicated are discussed.